When semiconductor devices are manufactured, in order to improve a manufacturing yield of semiconductor devices, pattern defect inspection is performed after a predetermined process such as the lithography. The pattern defects are classified into random defects caused by device dust and systematic defects caused depending on the type of a pattern.
In order to evaluate the systematic defects, patterns having a defect are first classified according to the type. At this time, a method such as design based binning (DEE) may be used as a pattern classifying method. In this method, after the defect inspection, patterns are classified such that defect coordinates are associated with pattern information (for example, design data) corresponding to the defect coordinates. Then, patterns having a defect are lined up and displayed in the descending order of the number of patterns detected by the defect inspection, and evaluation of patterns which are likely to have a defect is performed.
Meanwhile, when patterns having a defect are lined up based on the number of patterns in which a defect is detected, it is difficult to accurately extract a pattern having a defect which is small in the detected number but important. For this reason, it is desirable to accurately extract a pattern having a defect which is small in the detected number but important.